AI Services in Microsoft Azure – Fundamentals of Artificial Intelligence
AI Services in Microsoft Azure The main goal of Azure Applied AI Services is to help developers quickly find value in their data by integrating AI into their most important….
Latest Story
Azure Cognitive Services – Fundamentals of Artificial Intelligence
Azure Cognitive Services Azure Cognitive Services are a type of artificial intelligence (AI) service that is hosted in the cloud. With these services, software developers can add cognitive features to….
Azure Cognitive Search – Fundamentals of Artificial Intelligence
Azure Cognitive Search You will find hidden information in every piece of content and piece of data that you collect. Documents, media, images, and other types of content that go….
Introspective Practice – Fundamentals of Artificial Intelligence
Introspective Practice Now it’s time to check your knowledge before we move ahead with the next chapter. 1. You need to build a model that uses past data, such….
What Is Machine Learning? – Machine Learning Fundamental Concepts
What Is Machine Learning? In simple words, machine learning is all about the use of algorithms and statistical models to analyze and carve out inferences and patterns in data, which….
Dataset – Machine Learning Fundamental Concepts
Dataset A dataset is a group of related units of facts and information that is composed of unique elements that, however, can be manipulated as a single unit by a….
Validation Set – Machine Learning Fundamental Concepts
Validation Set The validation set is there to be used to train AI, with the goal of making it smart enough to learn from past mistakes and solve any problems….
Features and Labels – Machine Learning Fundamental Concepts
Features and Labels In simple words, a feature is an input, while a label is an output. For instance, you want to conduct research on a dataset containing population statistics…..
Machine Learning Workflow – Machine Learning Fundamental Concepts
Machine Learning WorkflowThe process of machine learning can be broken down into three easy-to-understand steps: (1) Data processing(2) Data modeling(3) DeploymentIt is very easy to understand the preceding three phases….
